Deployment
Docker & GPU
Docker support: Yes
GPU: Not required
Check the source notes below before assuming a GPU, transcoding workload or machine-learning feature is included in the baseline deployment.
Automation / AI / Dev
Open-source LLM app development platform combining AI workflow/RAG pipeline/agent capabilities and model management
Requirements
Badges are attached to each value. An estimate is never presented as an official project requirement.
| Resource | Minimum | Recommended |
|---|---|---|
| RAM | 4 GiB Official | 8 GiB Estimated |
| CPU | 2 cores Official | 4 cores Estimated |
| Disk | Not stated Not stated | Not stated Not stated |
Disk figures describe the application footprint recorded in the dataset. Personal media, documents, backups and other user data can require substantially more storage.
RunOnVPS sizing suggestion
8 GB RAM tier
This is our sizing suggestion, derived from Dify’s recommended RAM of 8 GiB. It is not an official requirement and it does not guarantee that every workload, plug-in set or media library will fit comfortably.
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Deployment
Docker support: Yes
GPU: Not required
Check the source notes below before assuming a GPU, transcoding workload or machine-learning feature is included in the baseline deployment.
Commercial alternative
Dify Cloud
Dify is catalogued here as a self-hosted alternative to Dify Cloud. Feature parity varies, so compare your required workflow before migrating.
Source check
Minimum CPU/RAM are official (README Quick start: CPU >= 2 Core / RAM >= 4 GiB; Docker Compose is the official easiest start). min_disk left blank: the official README does not state a minimum disk size. Recommended values are estimates (multi-container stack: api/worker/web/PostgreSQL/Redis/vector DB). GPU not required for Dify itself; it calls external or self-hosted model providers. GitHub stars 159377 on 2026-10-24.
Data source: https://github.com/langgenius/dify
Project repository: https://github.com/langgenius/dify
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